Overview

Dataset statistics

Number of variables12
Number of observations2774
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory281.7 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with unique_basket_sizeHigh correlation
basket_size is highly overall correlated with revenue and 1 other fieldsHigh correlation
distinct_stock_code is highly overall correlated with revenue and 3 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
revenue is highly overall correlated with basket_size and 3 other fieldsHigh correlation
total_products is highly overall correlated with basket_size and 3 other fieldsHigh correlation
total_purchases is highly overall correlated with distinct_stock_code and 2 other fieldsHigh correlation
unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
basket_size is highly skewed (γ1 = 44.87225707)Skewed
avg_ticket is highly skewed (γ1 = 51.90076813)Skewed
frequency is highly skewed (γ1 = 46.08548575)Skewed
returned is highly skewed (γ1 = 50.10197766)Skewed
customer_id has unique valuesUnique
recency has 34 (1.2%) zerosZeros
returned has 1481 (53.4%) zerosZeros

Reproduction

Analysis started2024-05-24 23:33:59.448847
Analysis finished2024-05-24 23:34:45.848895
Duration46.4 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2774
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15285.7
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:46.018905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12626.65
Q113815.25
median15242.5
Q316779.75
95-th percentile17950.35
Maximum18287
Range5940
Interquartile range (IQR)2964.5

Descriptive statistics

Standard deviation1714.9849
Coefficient of variation (CV)0.11219538
Kurtosis-1.2069151
Mean15285.7
Median Absolute Deviation (MAD)1483.5
Skewness0.015990788
Sum42402531
Variance2941173.2
MonotonicityNot monotonic
2024-05-24T23:34:46.315910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
14482 1
 
< 0.1%
17058 1
 
< 0.1%
17704 1
 
< 0.1%
16933 1
 
< 0.1%
13772 1
 
< 0.1%
16249 1
 
< 0.1%
14198 1
 
< 0.1%
13989 1
 
< 0.1%
17930 1
 
< 0.1%
Other values (2764) 2764
99.6%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18265 1
< 0.1%
18263 1
< 0.1%
18261 1
< 0.1%
18260 1
< 0.1%

revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2760
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2904.6492
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:46.612185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.557
Q1628.195
median1170.87
Q32423.86
95-th percentile7579.4915
Maximum279138.02
Range279101.46
Interquartile range (IQR)1795.665

Descriptive statistics

Standard deviation10927.083
Coefficient of variation (CV)3.7619287
Kurtosis331.96378
Mean2904.6492
Median Absolute Deviation (MAD)690.475
Skewness16.261241
Sum8057496.7
Variance1.1940114 × 108
MonotonicityNot monotonic
2024-05-24T23:34:46.900276image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1025.44 2
 
0.1%
745.06 2
 
0.1%
598.2 2
 
0.1%
1078.96 2
 
0.1%
731.9 2
 
0.1%
1353.74 2
 
0.1%
2053.02 2
 
0.1%
379.65 2
 
0.1%
1314.45 2
 
0.1%
331 2
 
0.1%
Other values (2750) 2754
99.3%
ValueCountFrequency (%)
36.56 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
77.4 1
< 0.1%
84.65 1
< 0.1%
90.3 1
< 0.1%
93.35 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency
Real number (ℝ)

ZEROS 

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.627974
Minimum0
Maximum372
Zeros34
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:47.197643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.419023
Coefficient of variation (CV)1.2082195
Kurtosis3.4321191
Mean56.627974
Median Absolute Deviation (MAD)23.5
Skewness1.8983643
Sum157086
Variance4681.1627
MonotonicityNot monotonic
2024-05-24T23:34:47.697554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.6%
4 87
 
3.1%
2 85
 
3.1%
3 85
 
3.1%
8 76
 
2.7%
10 67
 
2.4%
9 66
 
2.4%
7 65
 
2.3%
17 62
 
2.2%
22 55
 
2.0%
Other values (242) 2027
73.1%
ValueCountFrequency (%)
0 34
 
1.2%
1 99
3.6%
2 85
3.1%
3 85
3.1%
4 87
3.1%
5 43
1.6%
7 65
2.3%
8 76
2.7%
9 66
2.4%
10 67
2.4%
ValueCountFrequency (%)
372 1
 
< 0.1%
366 1
 
< 0.1%
360 1
 
< 0.1%
358 3
0.1%
354 1
 
< 0.1%
337 1
 
< 0.1%
336 2
0.1%
334 1
 
< 0.1%
333 2
0.1%
330 1
 
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct1155
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.801889
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:48.219214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134.241667
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)64.758333

Descriptive statistics

Standard deviation66.515011
Coefficient of variation (CV)0.84407889
Kurtosis3.6744362
Mean78.801889
Median Absolute Deviation (MAD)30
Skewness1.8283611
Sum218596.44
Variance4424.2467
MonotonicityNot monotonic
2024-05-24T23:34:48.727488image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 21
 
0.8%
46 18
 
0.6%
55 17
 
0.6%
31 16
 
0.6%
91 16
 
0.6%
49 16
 
0.6%
21 15
 
0.5%
42 15
 
0.5%
35 15
 
0.5%
14 14
 
0.5%
Other values (1145) 2611
94.1%
ValueCountFrequency (%)
1 9
0.3%
2 4
0.1%
2.861538462 1
 
< 0.1%
3 6
0.2%
3.330357143 1
 
< 0.1%
3.351351351 1
 
< 0.1%
4 5
0.2%
4.191011236 1
 
< 0.1%
4.275862069 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
364 1
 
< 0.1%
363 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

total_products
Real number (ℝ)

HIGH CORRELATION 

Distinct1632
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1697.8205
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:49.272681image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119
Q1330.25
median699.5
Q31478
95-th percentile4645.5
Maximum196844
Range196842
Interquartile range (IQR)1147.75

Descriptive statistics

Standard deviation6074.4301
Coefficient of variation (CV)3.5777812
Kurtosis438.72722
Mean1697.8205
Median Absolute Deviation (MAD)449
Skewness17.339197
Sum4709754
Variance36898701
MonotonicityNot monotonic
2024-05-24T23:34:49.847122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
246 8
 
0.3%
150 8
 
0.3%
200 7
 
0.3%
219 7
 
0.3%
260 7
 
0.3%
394 7
 
0.3%
272 7
 
0.3%
516 7
 
0.3%
300 7
 
0.3%
Other values (1622) 2698
97.3%
ValueCountFrequency (%)
2 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 2
0.1%
30 1
< 0.1%
32 1
< 0.1%
33 2
0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80997 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%

distinct_stock_code
Real number (ℝ)

HIGH CORRELATION 

Distinct341
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.28659
Minimum1
Maximum1785
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:50.418952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q129
median57
Q3105
95-th percentile239.35
Maximum1785
Range1784
Interquartile range (IQR)76

Descriptive statistics

Standard deviation98.70732
Coefficient of variation (CV)1.1851526
Kurtosis80.510195
Mean83.28659
Median Absolute Deviation (MAD)33
Skewness6.3465016
Sum231037
Variance9743.1349
MonotonicityNot monotonic
2024-05-24T23:34:50.962545image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 38
 
1.4%
24 37
 
1.3%
33 36
 
1.3%
26 36
 
1.3%
25 34
 
1.2%
18 33
 
1.2%
28 33
 
1.2%
30 32
 
1.2%
27 30
 
1.1%
23 29
 
1.0%
Other values (331) 2436
87.8%
ValueCountFrequency (%)
1 19
0.7%
2 13
0.5%
3 18
0.6%
4 18
0.6%
5 23
0.8%
6 19
0.7%
7 21
0.8%
8 24
0.9%
9 24
0.9%
10 19
0.7%
ValueCountFrequency (%)
1785 1
< 0.1%
1765 1
< 0.1%
1321 1
< 0.1%
1118 1
< 0.1%
883 1
< 0.1%
817 1
< 0.1%
717 1
< 0.1%
713 1
< 0.1%
699 1
< 0.1%
636 1
< 0.1%

total_purchases
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0529921
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:51.564801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.071603
Coefficient of variation (CV)1.4986973
Kurtosis183.94516
Mean6.0529921
Median Absolute Deviation (MAD)2
Skewness10.624664
Sum16791
Variance82.293981
MonotonicityNot monotonic
2024-05-24T23:34:51.997477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
Other values (45) 278
 
10.0%
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

basket_size
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1932
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.46514
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:52.361867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1103.33333
median172
Q3278.17381
95-th percentile585.55
Maximum40498.5
Range40497.5
Interquartile range (IQR)174.84048

Descriptive statistics

Standard deviation808.02308
Coefficient of variation (CV)3.2918039
Kurtosis2224.0987
Mean245.46514
Median Absolute Deviation (MAD)81
Skewness44.872257
Sum680920.29
Variance652901.3
MonotonicityNot monotonic
2024-05-24T23:34:52.707798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
86 9
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
82 7
 
0.3%
208 7
 
0.3%
105 7
 
0.3%
136 7
 
0.3%
197 7
 
0.3%
73 7
 
0.3%
Other values (1922) 2696
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
11.875 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%
2000 1
< 0.1%
1903.5 1
< 0.1%

unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1003
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.122355
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:53.061360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q110.127083
median17.296703
Q328.083333
95-th percentile56.64697
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.95625

Descriptive statistics

Standard deviation18.868378
Coefficient of variation (CV)0.85290999
Kurtosis24.16784
Mean22.122355
Median Absolute Deviation (MAD)8.2967033
Skewness3.1572707
Sum61367.414
Variance356.01568
MonotonicityNot monotonic
2024-05-24T23:34:53.370327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 44
 
1.6%
14 31
 
1.1%
11 29
 
1.0%
9 26
 
0.9%
1 26
 
0.9%
17.5 25
 
0.9%
10.5 25
 
0.9%
7.5 25
 
0.9%
9.5 24
 
0.9%
18 24
 
0.9%
Other values (993) 2495
89.9%
ValueCountFrequency (%)
1 26
0.9%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 21
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
203.5 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%
114 1
< 0.1%
110.3333333 1
< 0.1%
109.6666667 2
0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2772
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.33923
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:53.665626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.8527022
Q112.426548
median17.946876
Q325.074658
95-th percentile88.427443
Maximum56157.5
Range56155.349
Interquartile range (IQR)12.64811

Descriptive statistics

Standard deviation1071.0491
Coefficient of variation (CV)20.463601
Kurtosis2718.3215
Mean52.33923
Median Absolute Deviation (MAD)6.3338406
Skewness51.900768
Sum145189.02
Variance1147146.2
MonotonicityNot monotonic
2024-05-24T23:34:53.954072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
4.162 2
 
0.1%
6.269700855 1
 
< 0.1%
32.59775 1
 
< 0.1%
19.03048387 1
 
< 0.1%
28.55451613 1
 
< 0.1%
12.80068182 1
 
< 0.1%
6.396214689 1
 
< 0.1%
26.08797101 1
 
< 0.1%
17.98461538 1
 
< 0.1%
Other values (2762) 2762
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1225
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049692192
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:54.272648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0087463557
Q10.015758392
median0.024390244
Q30.041666667
95-th percentile0.11538462
Maximum17
Range16.99455
Interquartile range (IQR)0.025908275

Descriptive statistics

Standard deviation0.337595
Coefficient of variation (CV)6.7937233
Kurtosis2296.5219
Mean0.049692192
Median Absolute Deviation (MAD)0.010694545
Skewness46.085486
Sum137.84614
Variance0.11397038
MonotonicityNot monotonic
2024-05-24T23:34:54.569699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0625 17
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.6%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.07692307692 13
 
0.5%
0.02127659574 13
 
0.5%
0.02564102564 13
 
0.5%
Other values (1215) 2627
94.7%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1.142857143 1
 
< 0.1%
1 8
0.3%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

returned
Real number (ℝ)

SKEWED  ZEROS 

Distinct205
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.158976
Minimum0
Maximum80995
Zeros1481
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:34:54.882213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile98
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1564.3935
Coefficient of variation (CV)24.383081
Kurtosis2586.2541
Mean64.158976
Median Absolute Deviation (MAD)0
Skewness50.101978
Sum177977
Variance2447327.1
MonotonicityNot monotonic
2024-05-24T23:34:55.206881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
6 63
 
2.3%
5 55
 
2.0%
12 45
 
1.6%
8 39
 
1.4%
9 38
 
1.4%
Other values (195) 653
23.5%
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
5 55
 
2.0%
6 63
 
2.3%
7 38
 
1.4%
8 39
 
1.4%
9 38
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

Interactions

2024-05-24T23:34:41.766073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:33:59.856593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:03.018264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:07.229475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:11.015024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:15.922604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:19.474344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:23.995517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:27.354233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:30.684799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:34.265194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:38.494516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:42.037720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:00.114701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:03.273075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:07.658365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:11.270218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:16.177216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:19.872855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:24.254989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:27.619201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:30.964616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:34.617591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:38.768717image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:42.301519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:00.376764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:03.518677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:08.067165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:11.535521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:16.436523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:20.272573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:24.524024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:27.892400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:31.229488image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:34.976237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:39.026596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:42.570325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:00.649704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:03.777171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:08.511127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:11.793307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:16.718618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:20.661501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:24.789140image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:28.182767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:31.507214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:35.362899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:39.300458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:42.859961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:00.907317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:04.036582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:08.831384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:12.063869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:16.985517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:21.102173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:25.072589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:28.448861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:31.763579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:35.800132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:39.570279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:43.128136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:01.187984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:04.428996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:09.103826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:12.351096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:17.254168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:21.509589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:25.364998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:28.728149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:32.031443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:36.218547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:39.865575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:43.401366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:01.442998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:04.819098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:09.384810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:14.280698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:17.519520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:21.900124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:25.653235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:28.996741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:32.316522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:36.645435image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:40.141327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:43.675837image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:01.705777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:05.256064image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:09.656175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:14.561683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:17.814243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:22.335011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:25.940819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:29.293131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:32.579246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:37.094059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:40.414914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:43.958922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:01.967479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:05.675132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:09.936074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:14.838196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:18.091252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:22.799480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:26.235019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:29.568237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:32.842900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:37.426945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:40.704130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:44.246194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:02.232097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:06.053310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:10.187798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:15.108252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:18.367684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:23.186107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:26.503269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:29.832871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:33.142236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:37.702736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:40.972137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:44.498447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:02.480706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:06.444940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:10.448943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:15.369621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:18.632124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:23.444297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:26.767000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:30.102251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:33.489598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:37.959769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:41.226789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:44.765920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:02.740392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:06.832379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:10.743216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:15.648734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:19.028081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:23.706703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:27.050292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:30.394749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:33.900133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:38.225058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:34:41.491958image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-05-24T23:34:55.520705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
avg_recency_daysavg_ticketbasket_sizecustomer_iddistinct_stock_codefrequencyrecencyreturnedrevenuetotal_productstotal_purchasesunique_basket_size
avg_recency_days1.000-0.079-0.042-0.012-0.222-0.9520.223-0.214-0.366-0.342-0.4770.061
avg_ticket-0.0791.0000.199-0.141-0.4650.0810.0340.1890.2740.1960.090-0.627
basket_size-0.0420.1991.000-0.1200.3980.025-0.1040.2150.6020.7590.1250.431
customer_id-0.012-0.141-0.1201.0000.0080.0130.013-0.058-0.085-0.0780.0130.006
distinct_stock_code-0.222-0.4650.3980.0081.0000.142-0.3350.2810.6330.6320.5440.798
frequency-0.9520.0810.0250.0130.1421.000-0.1260.1750.2580.2390.322-0.070
recency0.2230.034-0.1040.013-0.335-0.1261.000-0.187-0.374-0.366-0.447-0.104
returned-0.2140.1890.215-0.0580.2810.175-0.1871.0000.4620.4270.4250.026
revenue-0.3660.2740.602-0.0850.6330.258-0.3740.4621.0000.9220.7620.281
total_products-0.3420.1960.759-0.0780.6320.239-0.3660.4270.9221.0000.7030.311
total_purchases-0.4770.0900.1250.0130.5440.322-0.4470.4250.7620.7031.0000.017
unique_basket_size0.061-0.6270.4310.0060.798-0.070-0.1040.0260.2810.3110.0171.000

Missing values

2024-05-24T23:34:45.173022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-24T23:34:45.635718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idrevenuerecencyavg_recency_daystotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
0178505391.21372.01.0000001733.021.034.050.9705888.73529418.15222217.00000040.0
1130473232.5956.052.8333331390.0105.09.0154.44444419.00000018.9040350.02830235.0
2125836705.382.026.5000005028.0114.015.0335.20000015.46666728.9025000.04032350.0
313748948.2595.092.666667439.024.05.087.8000005.60000033.8660710.0179210.0
415100876.00333.020.00000080.01.03.026.6666671.000000292.0000000.07317122.0
5152914623.3025.026.7692312102.061.014.0150.1428577.28571445.3264710.04011529.0
6146885630.877.019.2631583621.0148.021.0172.42857115.57142917.2197860.057221399.0
7178095411.9116.039.6666672057.046.012.0171.4166675.08333388.7198360.03352041.0
81531160767.900.04.19101138194.0567.091.0419.71428626.14285725.5434640.243316474.0
9160982005.6387.047.666667613.034.07.087.5714299.57142929.9347760.0243900.0
customer_idrevenuerecencyavg_recency_daystotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
561117290525.243.013.0404.092.02.0202.00000051.05.1494120.1428570.0
56201478577.4010.05.084.02.02.042.0000001.525.8000000.3333330.0
562117254272.444.011.0252.0100.02.0126.00000056.02.4325000.1666670.0
563717232421.522.012.0203.030.02.0101.50000018.011.7088890.1538460.0
563817468137.0010.04.0116.05.02.058.0000002.527.4000000.4000000.0
564913596697.045.07.0406.0133.02.0203.00000083.04.1990360.2500000.0
5655148931237.859.02.0799.072.02.0399.50000036.516.9568490.6666670.0
568014126706.137.03.0508.014.03.0169.3333335.047.0753330.75000050.0
5686135211092.391.04.5733.0312.03.0244.333333145.02.5112410.3000000.0
569615060301.848.01.0262.080.04.065.50000030.02.5153332.0000000.0